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Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar
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- M.Tech. (EC) - last date 28th April 2022
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- UG Admissions - All India Category - Admission Status Announced
Manjunath V. Joshi
Manjunath V. Joshi
PhD (Computer Vision), IIT Bombay
Contact Details
# B3, CEP 011, DAU, Gandhinagar, Gujarat, India – 382007
mv_joshi@dau.ac.in
Biography
Prof. Manjunath V. Joshi is a senior researcher and Institute Professor at Dhirubhai Ambani University (formerly, DA-IICT), Gandhinagar, with over four decades of academic experience in computer vision, machine learning, and signal processing. Beginning his teaching career in 1985 at Gogte Institute of Technology, Belgaum, he joined DA-IICT in 2005, where he served as Professor and as Dean of Research and Development (2020–2023). He completed his PhD in Computer Science area from IIT Bombay in 2004, winning the Best PhD Thesis Award, and his MTech (Communication Engineering) from IIT Bombay in 1989. Widely recognised as a pioneer in learning-based image super-resolution and inverse imaging, his research spans image restoration, hyperspectral unmixing, multi-resolution fusion, generative AI, adversarial robustness, and the emerging frontier of quantum machine learning applied to computer vision. He has authored or co-authored six research books published by Springer, Cambridge University Press, CRC Press, SPIE Press, and Morgan Claypool, graduated 9 PhD students, currently supervising 5 PhD students with 35+ MTech theses, and accumulated 2300+ citations with an h-index of 22. His international footprint includes extended research stays at the University of Trento (Italy), LSIIT Strasbourg (France), and FAU Erlangen (Germany). He has received the Dr. Vikram Sarabhai Award in Information Technology (Government of Gujarat, 2006–2007), the NVIDIA Hardware Grant, and has delivered training programmes for scientists at ISRO’s Space Applications Centre.
Specialization
Computer Vision, Image Super-Resolution, Hyperspectral Imaging, Remote Sensing, Generative AI, Diffusion Models, Adversarial Machine Learning, Quantum Machine Learning, Image Restoration, Inverse Problems, 3D Estimation, Spectral Unmixing, Spectrum Sensing
Publications
6 Books | 34+ Journal Papers | 78+ Conference Papers | 2300+ Citations | h-index: 22
Selected Recent Journal Publications:
- H. Tyagi, M. V. Joshi et al., “Matching Parameter Estimation for High-Power Inductively Coupled Plasma Sources Using Machine Learning Techniques,” Fusion Engineering and Design, vol. 208, Elsevier, Nov. 2024 (Q1).
- P. Gohel & M. V. Joshi, “Hybrid and Parallel GAN Architecture with Non-IID Noise Input,” The Journal of Supercomputing, Springer Nature, Jun. 2025 (Q2, IF: 2.7).
- H. Tyagi, M. V. Joshi et al., “Data-Driven Soft Sensor for Optical Intensity Estimation in High-Power Plasma Source,” IEEE Sensors Journal, vol. 25, Jul. 2025 (Q1).
- P. Garg, M. V. Joshi et al., “Multimodal Data Fusion by Integrating IoT-Enabled Sensors and Images for Jamun Crop Disease Detection,” IEEE Transactions on AgriFood Electronics, vol. 3, no. 2, Sep.–Oct. 2025.
- P. Garg, M. V. Joshi et al., “Transformer-Based Framework Using In-House Sensors and Lightweight Images for Accurate Plant Disease Classification,” IEEE Sensors Journal, vol. 26, no. 7, Apr. 2026 (Q1).
- H. Tyagi, M. V. Joshi et al., “A Data-Driven Reduced-Order Model for Plasma Density Estimation in a High-Power RF Ion Source,” Journal of Instrumentation, Apr. 2026 (Q3).
- P. Gohel & M. V. Joshi, “Quantum-Enhanced Framework for Single Image Super-Resolution Using Hybrid Quantum–Classical Learning,” Quantum Information Processing (QIP), Springer Nature, 2026 (Under Review, Q2).
- K. Patel, B. Makwana and M. V.Joshi, “Bloch–Wasserstein Generative Adversarial Network for Quantum State Learning,” Accepted at IEEE International Conference on Quantum Computing and Engineering (QCE26), Toronto, Canada, September 2026.
- K. Bhatia, B. Makwana, M. V. Joshi and S. Devendrababu, “Quantum Reservoir Computing with a Temporal Convolutional Readout for Optical Equalization and Forecasting,” Accepted at IEEE International Conference on Quantum Computing and Engineering (QCE26), Toronto, Canada, September 2026.
PREPRINTS:
P. Gohel & M. V. Joshi, “Quantum-Enhanced Framework for Single Image Super-Resolution Using Hybrid Quantum–Classical Learning,” Under Review, Quantum Information Processing (QIP), Springer Nature, 2026.
Teaching
In the teaching profession since 1985: 40 years spanning signal processing, communications, and modern AI. Courses taught include: Computer Vision, Machine Learning and Deep Learning, Quantum Machine Learning, Adversarial Machine Learning, Digital Image Processing, Digital Signal Processing, Statistical Communication Theory, Digital Communication, Signals and Systems. Also conducted Continuing Education Programmes for Scientists at ISRO/SAC Ahmedabad (2012, 2016, 2018) and for Professionals and Faculty (2020). Served as Visiting and Adjunct Faculty at IIT Gandhinagar (2010–2011) and Visiting Faculty at IIIT Vadodara (2017).